Mastering GIS Basics with ArcGIS | Batangas State University The National Engineering University

38 Hours

Hybrid

Overview

Gain valuable skills and insights into the world of data analytics and its applications in business and the public sector. This course covers the Data Analysis Lifecycle, the three types of data analytics (descriptive, predictive, and prescriptive), data visualization techniques, and the utilization of machine learning models. Through hands-on activities and Jupyter Notebooks, students will create data pipelines, perform exploratory data analysis, and develop data-driven storytelling abilities.

Total hours

Total: 38 Hours

Hybrid Learning: 20 Hours
Async Learning: 8 Hours
Skill-Based Assessment: 8 Hours
Final Exam via e-Learning Platform: 2 Hours

Course outline

Module 1: Data and the Internet of Things
Module 2: Fundamentals of Data Analysis
Module 3: Data Analysis
Module 4: Advanced Data Analytics and Machine Learning
Module 5: Storytelling with Data
Module 6: Architecture for Big Data and Data Engineering

What you'll learn

Extract valuable information and insights from IoT data, enabling businesses to make informed decisions based on real-time data streams.
Understand and execute the various steps involved in the Data Analysis Lifecycle, from data acquisition to visualization, ensuring accurate and effective analysis.
Differentiate between descriptive, predictive, and prescriptive data analytics, and leverage Python to apply these techniques to real-world datasets.
Develop skills in data manipulation and visualization using Python, enabling you to extract meaningful insights and communicate them effectively through data storytelling.
Gain an understanding of the evolution of data management technologies, from traditional SQL databases to modern NoSQL solutions, and explore distributed Big Data platforms like Apache Hadoop.